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   Articles with "unsupervised anomaly" as a keyword



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Improved autoencoder for unsupervised anomaly detection

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recommendations! Published in 2021 at "International Journal of Intelligent Systems"

DOI: 10.1002/int.22582

Abstract: Deep autoencoder‐based methods are the majority of deep anomaly detection. An autoencoder learning on training data is assumed to produce higher reconstruction error for the anomalous samples than the normal samples and thus can distinguish… read more here.

Keywords: detection; anomaly detection; improved autoencoder; unsupervised anomaly ... See more keywords

Unsupervised anomaly detection using generative adversarial networks in 1H-MRS of the brain.

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recommendations! Published in 2021 at "Journal of magnetic resonance"

DOI: 10.1016/j.jmr.2021.106936

Abstract: The applicability of generative adversarial networks (GANs) capable of unsupervised anomaly detection (AnoGAN) was investigated in the management of quality of 1H-MRS human brain spectra at 3.0 T. The AnoGAN was trained in an unsupervised manner… read more here.

Keywords: generative adversarial; detection; adversarial networks; anomaly detection ... See more keywords
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Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data Using Deep Learning: Early Detection of COVID-19 Outbreak in Italy

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recommendations! Published in 2020 at "IEEE Access"

DOI: 10.1109/access.2020.3022366

Abstract: Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection. Most real-world time series data have a spatial dimension… read more here.

Keywords: unsupervised anomaly; spatio temporal; anomaly detection; covid ... See more keywords

Unsupervised Anomaly Video Detection via a Double-Flow ConvLSTM Variational Autoencoder

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3165977

Abstract: With the rapid increase of video surveillance points in the market in recent years, video anomaly detection has gained extensive attention in the security field. At present, the distribution of normal and anomalous data is… read more here.

Keywords: unsupervised anomaly; detection; convlstm; variational autoencoder ... See more keywords

TCAD: Unsupervised Anomaly Detection Based on Global Local Representation Differences

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3216930

Abstract: Multivariate time series anomaly detection is of great interest because of its wide range of applications. Since it is difficult to obtain accurate anomaly labels, many unsupervised anomaly detection algorithms have been developed. However, it… read more here.

Keywords: global local; unsupervised anomaly; anomaly detection; local representation ... See more keywords

Constructing a Meta-Learner for Unsupervised Anomaly Detection

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recommendations! Published in 2023 at "IEEE Access"

DOI: 10.1109/access.2023.3274113

Abstract: Unsupervised anomaly detection (AD) is critical for a wide range of practical applications, from network security to health and medical tools. Due to the diversity of problems, no single algorithm has been found to be… read more here.

Keywords: meta; unsupervised anomaly; anomaly detection; meta learner ... See more keywords

Unsupervised Anomaly Detection for Medical Images Based on Multi-Hierarchical Feature Reconstruction

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3477719

Abstract: Unsupervised anomaly detection based on reconstruction is receiving focused research due to its low annotation requirement with gradually improving accuracy. However, the reconstruction quality and detection effect of existing methods still need to be improved.… read more here.

Keywords: detection; based multi; reconstruction; anomaly detection ... See more keywords

RaViT-AE: Unsupervised Anomaly Detection for Intelligent Cultural Heritage Monitoring Using Region-Attentive ViT Autoencoder

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3509988

Abstract: Unsupervised anomaly detection is well known for its ability to effectively identify and discern anomalies in data containing rare anomalies or diverse patterns, leading to broad applications across various research fields. However, this technology has… read more here.

Keywords: detection; region attentive; cultural heritage; anomaly detection ... See more keywords
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Robust Tracking via Learning Model Update With Unsupervised Anomaly Detection Philosophy

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recommendations! Published in 2023 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2022.3221723

Abstract: Template tracking is a typical paradigm to adaptively locate arbitrary objects in the tracking literature. Although existing works present diverse template updating approaches, one of the essential problems of template updating has not been solved… read more here.

Keywords: philosophy; template; unsupervised anomaly; anomaly detection ... See more keywords

Normal Image Guided Segmentation Framework for Unsupervised Anomaly Detection

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recommendations! Published in 2024 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2023.3327448

Abstract: Unsupervised anomaly detection is required to detect/segment anomalous samples/regions that deviate from the normal pattern while learning only through the normal sample category. Towards this end, this paper proposes a novel framework for anomaly detection… read more here.

Keywords: detection; guidance; framework; segmentation ... See more keywords

Online and Unsupervised Anomaly Detection for Streaming Data Using an Array of Sliding Windows and PDDs

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recommendations! Published in 2021 at "IEEE Transactions on Cybernetics"

DOI: 10.1109/tcyb.2019.2935066

Abstract: In this article, we propose an online and unsupervised anomaly detection algorithm for streaming data using an array of sliding windows and the probability density-based descriptors (PDDs) (based on these windows). This algorithm mainly consists… read more here.

Keywords: streaming data; online unsupervised; array; unsupervised anomaly ... See more keywords